The role of business intelligence in enhancing the insurance risk selection process

Abstract

The research aims to determine the correlation and impact relationship of business intelligence on insurance risk selection, assuming a statistically significant correlation between the two variables. The spatial boundaries of the research were represented by the Iraqi General Insurance Company in Baghdad, while the temporal boundaries included conducting the applied research on the study sample, collecting and analyzing data within a specified period, as well as distributing the questionnaire and completing the research. The human boundaries included department managers, assistant managers, section heads, underwriters, and producers in the studied company. The researcher adopted the descriptive-analytical approach, using a questionnaire as the primary tool for data collection, in addition to the statistical program (SPSS.26) for statistical processing. The analyses included the weighted arithmetic mean, standard deviation, coefficient of variation, Pearson’s simple correlation coefficient, multiple regression analysis, F-test, and T-test. Moreover, these systems contribute to improving pricing strategies, estimating losses, and enhancing risk management, leading to increased profitability and improved competitiveness of insurance companies. The research problem lies in the weak adoption of modern systems, such as business intelligence, in insurance companies, which affects their ability to select insurance risks—an essential process for maintaining the financial stability of these companies. The most significant finding of the research is that predictive analysis is the most influential factor in the insurance sector, enabling companies to anticipate future risks and optimize pricing strategies, thereby enhancing their ability to manage risks effectively.